Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
is well established that new developments in AI raise important ethical questions: how far should we expect end users to understand the ways in which algorithms work? Can/should we ensure that LLMs
-
project bridges two foundational fields in computer science and mathematics: Theory of Algorithms and Extremal Combinatorics. By integrating these areas, the project seeks to develop innovative
-
technological progress in our increasingly digital, data-driven world. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By
-
of the project is to develop new conceptualizations of what AI means to people, grounded in everyday life, and to assess democratic implications of emergent media technologies. The postdoc will design and conduct
-
intelligence (AI), and analyses changes in trust and understandings, at a time when AI becomes integrated into everyday media experiences. The goal of the project is to develop new conceptualizations of what AI
-
) for developing more reliable systems for Railway Transportation and contributes to Green Transportation. The goal is to identify early signs of wear or faults of the railway power system to improve maintenance
-
technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
-
technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data
-
to integrate large and complex molecular datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus
-
. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining